The present disclosure relates to an apparatus and an operating method for automatic detection of the face in a digital image and the localization of the eye region thereof. This extracted eye region then presents as a target region for iris recognition.
Electronic products such as a computer or a cellular phone include user's personal information in many cases. Also, the proliferation of electronic commerce using such electronic devices is becoming a modern trend. Thus, these electronic devices need to accurately identify the users. To this end, a method of recognizing a user by using a password and ID has been widely used. However, such a verification method has limitations with respect to personal information protection and anti-hacking. Thus, many alternatives to replace it have been proposed.
The latest trend for identity authentication is the usage of biometric systems which are being now gradually commercialized. A Biometric system has the capability to identify or verify each and every individual correctly by using physiological or behavioral characteristics possessed by the user. Towards this end, iris recognition is at present considered to be one of the best authentication processes available today. Iris recognition is stable and unique, at the same time it is non-invasive, offering unmatched accuracy. For such an iris recognition apparatus, an important inceptive step towards segmenting the iris within the eye is an efficient method for automatic detection of the eye region.
The first step towards finding the eye region corresponding to a face image is automatic detection of the face of an user in a given image. A highly accurate detection rate of the face and/or facial features like eye region is thus critical in the iris recognition apparatus. The problem of face detection has not received a great deal of attention, most research are focused on face recognition assuming that the image containing a single face is already available. Such techniques are unable to detect faces against a complex background where there are multiple occurrences of faces in an image. Automated face detection in a crowd is vital to separate the person from the background. The task is to detect the location and size of a human face irrespective of facial hair, facial expression, illuminating or facial occlusion like eyeglass and separate it from the non-face (which is the background). It is desirable to make use of the data obtained from the face detection process as a target for iris recognition, efficiently and quickly.